From discovering pretext to shipping 7 interactive effects across two sites in one session — explosion physics, bouncing bullets, and an animated crab named Clawd.

A 15KB JavaScript library just solved one of the oldest architectural debts in web development — knowing how tall text will be without asking the browser to reflow the entire page.

I wanted a voice-to-notes pipeline. The internet said build a watchOS app. A friend who tried said don't. Thirty minutes later — with Claude Code doing the heavy lifting — I had a zero-cost, zero-dependency solution using nothing but Voice Memos, iCloud, and one Gemini API call.

First principles on AI: every trend, traced to its root, is about whether there's enough compute — and whether it's good enough

How I built a hybrid read+write WeChat automation pipeline on macOS — the tools, the architecture, and the 6 pitfalls that'll save you hours

Three demand curves, one deflation trend, and why compute is the new oil

A style library, no matter how large, can't cover everyone's taste. Some users want to write like an author who isn't in the library. Some want the voice of one specific article, not a generalized style. The solution: real-time style extraction. Give the AI any reference article, and it clones the writing DNA on the fly.

One style guide fixed translation-ese, but a tech review shouldn't sound like social commentary. Different content needs different voices. I developed a systematic method for 'stealing' any author's writing style — collecting articles, dissecting patterns, and extracting a structured Style Profile. Here's the full process, demonstrated with a real example.

My blog had 83 Chinese posts — all of them read like translated English. Stiff, formal, academic. So I studied China's best WeChat writers, distilled their craft into a 435-line writing system, and fed it to Claude as a system prompt. Then I rewrote every single post. This is the story of that guide.

A former Google TPU engineer who worked on V7 and V8 revealed how TPU actually competes with Nvidia. The answer isn't about chip specs — it's about system-level design, software co-optimization, and a fundamentally different philosophy. Apple, Anthropic, and Meta are all using TPU now. Here's what that means.